Responsibilities
- Lead Design Data Architecture – Drive the development of the Data Mesh layer by designing robust data models and building pipelines that integrate into the company's federated data strategy, ensuring scalable and governed data ownership.
- Define AI Agentic Workflows – Design and implement AI-powered agentic workflows for data transformation and exploration, accelerating analytical capabilities and enabling self-service for key stakeholders.
- Build High-Impact Visualisation Tools – Define key metrics and develop dashboards and reports (using tools like Hex or Looker) that communicate analytical insights effectively.
- Drive Decision-Making Through Data – Analyse complex datasets to identify patterns impacting the consumer funnel (Acquisition, Engagement, Retention, Monetisation) and partner with Marketing Managers to maximise ROI.
- Partner with Key Stakeholders – Act as a strategic partner for Marketing, Finance, Operations, and Product, bridging the gap between technical data and business goals.
- Drive Testing Initiatives – Own the end-to-end testing pipeline, from opportunity identification to experiment design and recommendation delivery.
Requirements
- Relevant Experience – 5+ years in data-related roles (Data Engineering, Analytics, BI) with at least 3 years of hands-on experience in high-volume or big data environments.
- Technical Proficiency – Strong command of SQL, dbt, and Python.
- Data Modelling & Mesh Expertise – Hands-on experience in data modelling, ETL, data governance, and Data Mesh implementation at scale.
- AI Fluency — Comfortable using AI tools day-to-day for analytics, automation, and generating ad-hoc analyses, C-level summaries, marketing campaign suggestions, and business cases efficiently using AI agents.
- Analytical & Problem-Solving Skills – Comfortable with ambiguity, able to break down complex problems into focused workstreams and deliver evidence-based answers.
- Stakeholder Management & Communication – Able to independently lead initiatives across diverse business domains and translate technical findings into clear, actionable recommendations.
- Digital Consumer Lifecycle Knowledge – Solid understanding of consumer lifecycle (Acquisition, Activation, Retention, Churn) and user economics (ARPU, CAC, LTV).
Nice to Have
- Experience with Git and notebook-based analytics (e.g., Jupyter) is a plus.
- Basic to mid-level proficiency with Claude is a strong plus.
- Experience interacting with agents programmatically via APIs is a plus.
Benefits
- Health (Private insurance for you and your family, psychological support with Serenis, mental health workshops)
- Financial resources (Stock Option Plan, Meal vouchers, Relocation support if you’re moving countries)
- Growth and development (Professional development programs, Internal mobility, Language courses with Preply)
- Flexibility (Unlimited PTO, Hybrid working policy*, Flexible working hours)
- Family (Enhanced parental leave, Additional leave for child sickness)
Work Arrangement
Hybrid
Additional Information
- Hybrid working policy: three days per week in-office (Tuesday and Thursday + 1 of your choice), with the option to request extra remote time.
- Relocation support if you’re moving countries.
